Motion correction method and device, image reconstruction method and device and PET equipment

Abstract

The invention discloses a motion correction method, an image reconstruction method and device and PET equipment, and further relates to related electronic equipment and a storage medium. The motion correction method can be applied to PET equipment and comprises the steps that detection data obtained by detecting a moving target object through multiple detectors are obtained, and the detection data comprise coincidence event data on a response line; performing motion correction on at least part of the coincidence event data on the response line according to the motion track of the target object to obtain first correction data on the correction response line; and determining second correction data for image reconstruction according to intersection information of the correction response line of the first correction data and the detector and / or the virtual detector. According to the scheme provided by the invention, the virtual detector is added, a large number of events which are to be discarded after motion correction are fully utilized and introduced into the reconstruction process, and the system sensitivity is improved by combining a data recovery mode.

Description

Technical Field

[0001] The present application relates to the field of data processing, and specifically to a motion correction method, an image reconstruction method, an apparatus, and a PET device, and also to related electronic equipment and storage media. Background Art

[0002] Positron Emission Tomography (PET) technology is currently the world's most advanced molecular imaging technology. It can non-invasively, quantitatively and dynamically evaluate the metabolic levels, biochemical reactions and functional activities of various functional organs in the body by imaging compounds labeled with radionuclides in the body with high sensitivity and accuracy.

[0003] The working principle of PET is to label a radioactive nuclide that emits positrons on a compound that can participate in the blood flow or metabolic process of living tissue, and inject the compound labeled with the radioactive nuclide into the body. The positrons emitted by the decay of the radioactive nuclide in the body combine with the negative electrons in the body, resulting in an electron pair annihilation event, which produces two gamma photons with equal energy and opposite directions, so they can be detected by the detector probe. If the two scintillating crystals located on the line of response (LOR) in the detector detect two gamma photons within the specified coincidence time window (for example, 0 to 15 nanoseconds) and energy window (400 to 600 keV), the event of detecting these two gamma photons can be called a coincidence event. Subsequently, the PET image of the subject can be reconstructed based on the information of the coincidence event.

[0004] When using medical imaging equipment including PET for imaging, since the imaging target, such as the human body or animal body, cannot remain completely still, motion artifacts may appear in the reconstructed image, affecting the image reconstruction effect. Therefore, the current prior art proposes to achieve PET imaging for moving targets through motion correction technology.

[0005] The current motion correction algorithms include correction for rigid motion and non-rigid motion. For rigid motion correction, there are motion correction techniques based on projection domain and motion correction techniques based on image domain.

[0006] The motion correction technology based on projection domain data includes an event by event (EBE) motion correction algorithm. According to the motion information of each data frame relative to the reference frame, the LOR of each event in the data frame is spatially mapped and restored to the LOR corresponding to the reference frame. The projection data after motion correction is obtained by integration and used for image reconstruction, finally obtaining a reconstructed image after motion compensation.

[0007] However, the range of LORs that can be detected by the PET detector is limited by the maximum annular difference and the maximum radial distance. After the spatial transformation of LORs, two data loss situations may occur: 1. Some LORs that can be detected at the reference position at the initial moment may move out of the detection field of view (FOV) due to movement and cannot be detected, resulting in data loss; 2. LORs that are not at the reference position at the initial moment enter the FOV due to movement and are detected, but are discarded after motion correction because they do not correspond to the actual detector. The first situation will cause image artifacts, and the second situation will not cause image artifacts, but may cause a loss of image signal-to-noise ratio.

[0008] In addition, especially in flat-panel PET devices, the data or images processed by motion correction still have the problem of image deformation caused by parallax effect.

[0009] The content of the background technology description is only for facilitating understanding of the relevant technology in this field and is not regarded as an admission of the prior art. Summary of the invention

[0010] Therefore, the present application intends to provide a motion correction method, an image reconstruction method, an apparatus, a PET device, and related electronic devices and storage media, which can solve at least one problem existing in the prior art.

[0011] In a first aspect, a motion correction method is provided, which is applied to a PET device, wherein the PET device includes a plurality of detectors and defines at least one virtual detector. The motion correction method comprises:

[0012] Acquire detection data obtained by the plurality of detectors detecting the moving target object, wherein the detection data includes coincident event data on the response line;

[0013] According to the motion trajectory of the target object, motion correction is performed on at least part of the coincident event data on the response line to obtain first corrected data on the corrected response line; and

[0014] Second correction data for image reconstruction are determined according to intersection information of the correction response line of the first correction data and the detector and / or the virtual detector.

[0015] In an embodiment of the present application, the conforming event data includes response line endpoint position data conforming to the event; the first correction data includes corrected response line endpoint position data; and the second correction data includes corrected intersection position data.

[0016] In the embodiment of the present application, the acquiring of detection data obtained by the multiple detectors detecting the moving target object includes:

[0017] Acquire detection data with depth of interaction (DOI) information to determine the response line endpoint position data of the coincident event.

[0018] In an embodiment of the present application, performing motion correction on at least part of the conforming event data on the response line according to the motion trajectory of the target object to obtain first correction data on the correction response line includes:

[0019] determining a reference detection position among a plurality of detection positions of the motion trajectory;

[0020] According to the motion trajectory of other detection positions relative to the reference detection position, the response line endpoint positions on the response lines located at the other detection positions are spatially transformed to obtain the corrected response line endpoint positions.

[0021] In an embodiment of the present application, the motion correction method further includes:

[0022] The coincident event data located on the response line of the reference detection position is used as non-corrected data for image reconstruction.

[0023] In the embodiment of the present application, the acquiring of detection data obtained by the multiple detectors detecting the moving target object includes:

[0024] The detection data is divided into a plurality of data frames corresponding to a plurality of detection positions.

[0025] In an embodiment of the present application, determining a reference detection position among a plurality of detection positions of the motion trajectory includes:

[0026] A reference frame is determined among the multiple data frames, and the target object is located at the reference detection position in the reference frame.

[0027] In the embodiment of the present application, the spatial transformation of the response line endpoint position on the response line located at the other detection position according to the motion trajectory of the other detection position relative to the reference detection position to obtain the corrected response line endpoint position includes:

[0028] According to the motion information of other data frames relative to the reference frame, each response line that meets the event in each of the other data frames is spatially mapped and converted into a correction response line corresponding to the reference frame.

[0029] In an embodiment of the present application, determining second correction data for image reconstruction according to intersection information of a correction response line of the first correction data with the detector and / or the virtual detector includes:

[0030] The actual intersection position of the correction response line and / or its extension line with the detection surface of the detector and / or the virtual detection surface of the virtual detector is determined as the correction intersection position.

[0031] In an embodiment of the present application, determining second correction data for image reconstruction according to intersection information of a correction response line of the first correction data with the detector and / or the virtual detector includes:

[0032] Determine the crystal and / or virtual crystal where the correction response line and / or its extension line intersects with the detection surface of the detector and / or the virtual detection surface of the virtual detector, and take the center of the intersecting crystal and / or virtual crystal as the correction intersection position.

[0033] In an embodiment of the present application, the motion correction method further includes:

[0034] Determining the motion trajectory of the target object specifically includes:

[0035] Acquiring a plurality of captured images of the moving target object;

[0036] extracting two-dimensional feature points from the plurality of captured images;

[0037] Matching the two-dimensional feature points of the multiple captured images and converting them into three-dimensional feature points;

[0038] The three-dimensional feature points of different image frames of the plurality of captured images are matched to construct a rotation-translation (RT) matrix representing relative motion information of the different image frames.

[0039] In an embodiment of the present application, the motion correction method further includes:

[0040] The target object is made to move along a given motion trajectory, and the motion trajectory is stored.

[0041] In a second aspect, an image reconstruction method is provided, which may include:

[0042] Using multiple detectors to detect the moving target object to obtain detection data;

[0043] Processing the detection data using the motion correction method according to the first aspect to obtain second correction data;

[0044] An image reconstruction is performed using the processed detection data, the processed detection data including the second correction data.

[0045] In an embodiment of the present application, the image reconstruction method further includes:

[0046] Acquire non-corrected data using the motion correction method according to the embodiment of the present application;

[0047] The processed detection data includes the second corrected data and the non-corrected data.

[0048] In the embodiment of the present application, the processed detection data is detection data in list-mode format.

[0049] In an embodiment of the present application, the image reconstruction method, before image reconstruction, further includes:

[0050] setting a sinusoidal pattern encoding for said processed detection data;

[0051] Based on the sinusoidal encoding, the processed detection data is processed to obtain detection data in a sinusoidal form.

[0052] In a third aspect, a motion correction device is provided, which is applied to a PET device, wherein the PET device includes a plurality of detectors and defines at least one virtual detector. The motion correction device includes:

[0053] an acquisition unit configured to acquire detection data obtained by the plurality of detectors detecting the moving target object, wherein the detection data includes coincident event data on the response line;

[0054] A first correction unit is configured to perform motion correction on at least part of the coincident event data on the response line according to the motion trajectory of the target object to obtain first correction data on the corrected response line; and

[0055] The second correction unit is configured to determine second correction data for image reconstruction according to intersection information between the correction response line of the first correction data and the detector and / or the virtual detector.

[0056] In an embodiment of the present application, the plurality of detectors circumferentially surround the target object, and the at least one virtual detector includes an end virtual detector located at at least one axial end of the plurality of detectors.

[0057] In an embodiment of the present application, the at least one virtual detector includes a pair of end virtual detectors located at two axial ends of the plurality of detectors.

[0058] In an embodiment of the present application, the multiple detectors are multi-panel detectors or annular detectors, and the end virtual detector has a polygonal shape corresponding to the end opening of the multi-panel detector or a circular shape corresponding to the end opening of the annular detector.

[0059] In an embodiment of the present application, the multiple detectors only partially surround the target object in the circumferential direction, and the at least one virtual detector includes a circumferential virtual detector arranged in a circumferential non-surrounding area of ​​the multiple detectors.

[0060] In an embodiment of the present application, the at least one virtual detector further includes one or two end virtual detectors located at one or both axial ends of the multiple detectors and the circumferential virtual detector.

[0061] In an embodiment of the present application, the plurality of detectors are multi-flat panel detectors with circumferential notches, and the circumferential virtual detector has the same shape as the detectors and completes the circumferential notches.

[0062] In an embodiment of the present application, the multiple detectors are partial annular detectors with circumferential gaps, and the circumferential virtual detector has a ring segment shape that fills the circumferential gap.

[0063] In an embodiment of the present application, each of the detectors includes a crystal array having a detection surface, the virtual detector includes a virtual crystal array having a virtual detection surface, or the virtual detector is composed of a virtual detection surface of a virtual crystal array.

[0064] In a fourth aspect, an image reconstruction apparatus is provided, which may include:

[0065] A detection unit is configured to detect a moving target object using a plurality of detectors to obtain detection data;

[0066] a motion correction unit, configured to process the detection data using the motion correction method according to the embodiment of the present application to obtain second correction data;

[0067] The image reconstruction unit is configured to perform image reconstruction using the processed detection data, wherein the processed detection data includes the second correction data.

[0068] In a fifth aspect, a PET device is provided, comprising a plurality of detectors and a motion correction unit; wherein the PET device is further defined to have at least one virtual detector; wherein the motion correction unit is configured to implement the motion correction method according to the first aspect.

[0069] In a sixth aspect, an electronic device is provided, characterized in that it includes: a processor and a memory storing a computer program, and the processor is configured to implement the method described in the embodiment of the present application when running the computer program.

[0070] In a seventh aspect, a storage medium is provided, wherein the storage medium stores a computer program, and the computer program is configured to implement the method described in the embodiments of the present application when executed.

[0071] The solution of the embodiment of the present application constructs at least one virtual detector, performs response line correction on the detection data of the moving target detected by the detector, and determines the motion correction data for image reconstruction based on the intersection information of the corrected response line with the detector and / or the virtual detector; this makes full use of a large number of motion-corrected events that should have been discarded, introduces them into the reconstruction process, and improves the system sensitivity by combining data recovery, thereby alleviating or solving the technical problem of insufficient utilization of conforming detection data in known technologies.

[0072] In a further solution of an embodiment of the present application, the problem of deformation caused by parallax effect still existing in the motion-corrected data or images in the known technology is alleviated or solved by directly combining the response depth (DOI) information in the original detection data used for motion correction.

[0073] The optional features and other effects of the embodiments of the present application are partially described below, and partially can be understood by reading this document. BRIEF DESCRIPTION OF THE DRAWINGS

[0074] The embodiments of the present application are described in detail with reference to the accompanying drawings. The elements shown are not limited by the proportions shown in the accompanying drawings. The same or similar reference numerals in the accompanying drawings represent the same or similar elements, wherein:

[0075] Figure 1 A flow chart of a motion correction method according to an embodiment of the present application is shown;

[0076] Figure 2 A flow chart of a motion correction method according to an embodiment of the present application is shown;

[0077] Figure 3 A flow chart of a motion correction method according to an embodiment of the present application is shown;

[0078] Figure 4 A schematic diagram of the structure of a detector and a virtual detector applicable to a PET device according to an embodiment of the present application is shown;

[0079] Figure 5 A schematic diagram of the structure of a detector and a virtual detector applicable to a PET device according to an embodiment of the present application is shown;

[0080] Figure 6 A schematic diagram of the structure of a detector and a virtual detector applicable to a PET device according to an embodiment of the present application is shown;

[0081] Figure 7 A schematic diagram of the structure of a detector and a virtual detector applicable to a PET device according to an embodiment of the present application is shown;

[0082] Figure 8A schematic diagram of the structure of a detector and a virtual detector applicable to a PET device according to an embodiment of the present application is shown;

[0083] Fig. 9A A schematic diagram of the structure of a detector and a virtual detector applicable to a PET device according to an embodiment of the present application is shown;

[0084] Fig. 9B A schematic diagram of a detector and a (simplified) virtual detector structure applicable to a PET device according to an embodiment of the present application is shown;

[0085] Fig. 9C A (simplified) virtual detector structure schematic diagram applicable to a PET device according to an embodiment of the present application is shown;

[0086] Fig.10 A schematic diagram of the structure of a detector and a virtual detector applicable to a PET device according to an embodiment of the present application is shown;

[0087] FIG. 11A to FIG. 11C A schematic diagram of the structure of a detector and a virtual detector applicable to a PET device according to an embodiment of the present application is shown;

[0088] Fig.12 A comparative schematic diagram showing the effect of using or not using the depth of interest (DOI) information on the parallax effect deformation;

[0089] Fig.13 A schematic diagram of motion correction based on event by event (EBE) which can be applied to the motion correction method according to an embodiment of the present application is shown;

[0090] Fig.14 A schematic diagram showing motion correction based on intersection information that can be applied to the motion correction method according to an embodiment of the present application is shown;

[0091] Fig.15 A flowchart of an image reconstruction method according to an embodiment of the present application is shown;

[0092] Fig.16 A module diagram of a motion correction device according to an embodiment of the present application is shown;

[0093] Fig.17 A module diagram of an image reconstruction device according to an embodiment of the present application is shown;

[0094] Fig.18 A schematic diagram of an electronic device according to an embodiment of the present application is shown;

[0095] Fig.19 Data in list mode format is shown. DETAILED DESCRIPTION

[0096] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with specific implementation methods and drawings. Here, the exemplary implementation methods of the present invention and their descriptions are used to explain the present invention, but are not intended to limit the present invention.

[0097] As used herein, the term "including" and its variations mean open inclusion, i.e., "including but not limited to". Unless otherwise stated, the term "or" means "and / or". The term "based on" means "based at least in part on". The terms "an example embodiment" and "an embodiment" mean "at least one example embodiment". The term "another embodiment" means "at least one additional embodiment". The terms "first", "second", etc. may refer to different or the same objects. Other explicit and implicit definitions may also be included below.

[0098] The motion correction and image reconstruction scheme provided in this application relates to radiation tomography technology, in particular to positron emission tomography (PET) technology, and can be applied to a variety of fields, such as medical imaging, high-energy physics, oil and mineral exploration, security inspection and other fields.

[0099] As mentioned above, in the technology known to the inventors, when performing motion correction on projection domain data, the following problem may occur: the LOR that is not at the reference position at the initial moment may be captured by the detection field of view (FOV) of the PET device due to motion, and generate counts; however, after motion correction, since it does not correspond to the actual detector, this part of the counts will not be counted, resulting in data loss. Although this situation will not cause image artifacts, it may cause a loss of image signal-to-noise ratio.

[0100] In addition, when performing motion correction on projection domain data, there may be a problem that the initial moment can be captured by the detector structure of the PET device, but due to movement, it moves out of the FOV and cannot be detected, resulting in data loss. This situation will cause the counts on some response lines (LORs) to decrease, which may cause artifacts in the reconstructed image, affecting the quality of the final reconstructed image and the accuracy of quantitative analysis.

[0101] In the technology known to the inventors, the data loss caused by the movement out of the detection range is compensated by a global correction factor.

[0102] Specifically, the time t that each LOR in the final projection data obtained after LOR spatial transformation moves out of the FOV can be estimated out-of-FOV , and assuming that the count rate on each LOR is constant during the entire data acquisition process with a total time T, the correction factor for each LOR can be calculated.

[0103] In the technology known to the inventors, the number of coincidence events on the response line P after data correction can be calculated according to the following formula (1):

[0104]

[0105] Among them, N p represents the number of coincidence events detected by the response line P during the entire data acquisition process, t out-of-FOV It is the time when the response line P moves out of the detection range.

[0106] The above content can refer to P. Bühler, U. Just, E. Will, J. Kotzerke and J. Van Den Hoff, "Anaccurate method for correction of head movement in PET", IEEE Trans. Med. Imaging, Vol. 23, No. 9, pp. 1176-1185, 2004, doi: 10.1109 / TMI.2004.831214., which is incorporated herein by reference in its entirety in a non-contradictory manner.

[0107] Furthermore, in order to determine whether the LOR in the final projection data will move out of the FOV after a given spatial transformation, the LOR at the reference position can be subjected to inverse motion compensation to make it correspond to the position of each data frame, and to determine whether it is within the FOV. Inverse motion compensation is performed on all LORs at the reference position in turn according to the motion information of each data frame relative to the reference position, and it is determined whether it has moved out of the FOV, and the time t at which the LOR moves out of the detection range in the projection data is updated. out-of-FOV .

[0108] By multiplying the motion-corrected data by a global correction factor, some events that are discarded after the LOR spatial transformation are compensated. The global correction factor formula is shown below (2):

[0109]

[0110] Among them, H h represents the total number of detected coincident event pairs, H l Represents events discarded during LOR spatial transformation and reassembly.

[0111] The above content can refer to VW Zhou, AZ Kyme, SR Meikle and R. Fulton, "An event-driven motion correction method for neurological PET studies of awake laboratory animals", Mol. Imaging Biol., Volume 10, Issue 6, Pages 315-324, 2008, doi: 10.1007 / s11307-008-0157-0., which is incorporated herein by reference in its entirety in a non-contradictory manner.

[0112] In addition, the data can be incorporated into the reconstruction process by moving the system response matrix. The above content can be referred to A. Rahmim et al., "Motion compensation in histogram-mode and list-mode EM reconstructions: beyond the event-driven approach", IEEE Trans. Nucl. Sci., Volume 51, Issue 5, Pages 2588-2596, October 2004, doi: 10.1109 / TNS.2004.835763., which is incorporated herein by reference in its entirety in a non-contradictory manner.

[0113] However, the above-mentioned motion correction technologies cannot effectively handle the problem of data loss caused by the data being initially out of the detection range and then moving into the detection range.

[0114] In addition, as mentioned above, in the motion correction technology known to the inventors, the data or images processed by motion correction still have the problem of image deformation caused by the parallax effect, which is particularly prominent in flat-panel PET devices. As an explanation, Fig.12 As shown, it is assumed that the solid line AB represents a pair of gamma photon flight trajectories that match the event. When the gamma photon flies along the solid line, the gamma photon does not deposit as soon as it encounters the crystal, but will only deposit after flying for a while. At this time, the system detects that the gamma photon is deposited at crystals 2 and 4, so the photoelectric conversion device detects the photon deposition at crystals 2 and 4, and records the count of the coincident event in the LOR (A'B') composed of the surface center connecting line of crystals 2 and 4. In other words, the dotted line A'B' is an erroneously determined LOR. It can be seen that the LOR (A'B') is far from the flight trajectory of the gamma photon, so the LOR is an erroneous LOR, which can also be called the parallax effect. Therefore, the corrected data or image obtained after performing motion correction based on the coincident event data of the erroneously determined LOR (A'B') still has the problem of image deformation caused by the parallax effect.

[0115] In this regard, the embodiment of the present application makes full use of a large amount of data that was initially not in the detection range and moved into the detection range (matching events) and should have been discarded by adding a virtual detector, introduces it into the reconstruction process, and greatly improves the system sensitivity by combining it with data recovery.

[0116] In addition, in the preferred embodiment of the present application, by combining the detection data used for motion correction with the depth of interaction (DOI) information, the problem of image deformation caused by the parallax effect still existing in the data or image after motion correction is overcome.

[0117] Compared with the known methods, in the embodiments of the present application, Figure 1 Combination Figures 2 to 11C As shown, a motion correction method is provided, which can be applied to a PET device, the PET device includes multiple detectors and is defined with at least one virtual detector. Accordingly, an embodiment of the present application also provides a PET device defined with the above virtual detector, as further described below.

[0118] The specific embodiments of the present application will be described in detail below with reference to the accompanying drawings.

[0119] like Figure 1 As shown, the motion correction method of the embodiment of the present application may include optional step S1:

[0120] S1: Determine the motion trajectory of the moving target object.

[0121] In some embodiments, the optional step S1 of determining the motion trajectory may be performed simultaneously with the step S2 of acquiring detection data described below.

[0122] like Figure 2 Schematically shown, the optional step S1 may specifically include:

[0123] S11: Acquire a plurality of captured images of the moving target object;

[0124] S12: extracting two-dimensional feature points from the plurality of captured images;

[0125] S13: Matching the two-dimensional feature points of the plurality of captured images and converting them into three-dimensional feature points;

[0126] S14: Matching three-dimensional feature points of different image frames of the multiple captured images, and constructing a rotation-translation (RT) matrix representing relative motion information of different image frames.

[0127] In some embodiments, two image capturing devices, such as cameras, may be used to capture images of the target object. In a preferred embodiment, for example, two captured images (such as axial front-to-back captured images) are captured from two axial ends of the detector structure of the PET device, each of which includes multiple image frames (correspondingly, one captured image may also be referred to as two groups of (captured) images (frames)).

[0128] Next, the scale-invariant feature transform (SIFT) method can be used to extract two-dimensional feature points from the captured image, and the two-dimensional feature points of the two sets of captured images are matched, and three-dimensional feature points are obtained through triangulation conversion processing.

[0129] Next, the three-dimensional feature points in different image frames in these captured images can be matched. In a specific example, an initial (reference) image frame can be determined in the image frame. Thus, the remaining image frames can be matched with the three-dimensional feature points of the initial image frame. In addition, the relative motion information between different image frames can be obtained by the singular value decomposition (SVD) method, which can be represented by a rotation-translation (RT) matrix. In the above specific example, the RT matrix of other picture frames relative to the initial (reference) image frame can be determined.

[0130] In this embodiment, in order to distinguish the reconstructed image, the image that obtains the motion information of the target object is called the captured image. In addition, it will be understood that in this embodiment, when the detection data is also divided into multiple (data) frames, the multiple data frames can correspond to the multiple image frames in time, or the multiple image frames have a frame number greater than the data frame (higher frame rate). It will also be understood that the initial (reference) frame of the image frame is optional, and the initial (reference) frame of the data frame also optionally corresponds to or does not correspond to the initial (reference) frame of the image frame, which all fall within the scope of the present invention.

[0131] In an alternative embodiment of the present application, the motion trajectory of the target object may be given. For example, as an alternative to S1, the motion correction method may include an alternative step S1' (not shown): causing the target object to move along a given motion trajectory and storing the motion trajectory.

[0132] Continue to refer Figure 1 The motion correction method of the embodiment of the present application may further include steps S2 to S4.

[0133] Step S2 will be described in detail below:

[0134] S2: Acquire detection data obtained by the multiple detectors from detecting the moving target object, wherein the detection data includes coincident event data on the response line.

[0135] As described above, in some embodiments, the motion trajectory may optionally be determined while acquiring the detection data.

[0136] In an embodiment of the present application, the coincidence event data includes the response line endpoint position data of the coincidence event. As mentioned above, in the electron pair annihilation event in the PET device, two gamma photons of equal energy and opposite directions will be generated, and if the two scintillation crystals located on the response line (LOR) in the detector detect two gamma photons in the prescribed coincidence time window (e.g., 0-15 nanoseconds) and energy window (400-600keV), respectively, then the event of detecting the two gamma photons can be called a coincidence event. Accordingly, the coincidence event data may include the deposition position data of the two gamma photons in the coincidence event, and can be used to determine the response line endpoint position data of the coincidence event, which is a known technology and is not repeated here. In an embodiment of the present application, it will be understood that the response line endpoint position of the coincidence event may not be the (actual) deposition position of the gamma photon, for example, the center of the corresponding crystal where the response line intersects with the crystal surface (detection surface). And the crystal intersecting the LOR can be adjusted according to the actual depth position determined by the optional DOI information, as further described below. Furthermore, it will be appreciated that the DOI-based corrected (adjusted) LOR described with respect to step S2 is different from the motion-corrected corrected LOR described with respect to step S3.

[0137] In a specific embodiment, the detection data, more specifically the event data, may be in a list format, such as Fig.19 Accordingly, the detection data in the list mode format, more specifically the event data, includes position information, which can record the position (coordinates) of the endpoint of the response line corresponding to the event.

[0138] In an alternative specific embodiment, the detection data, more specifically the event data, may be a sinogram, and the sinogram may be converted and processed in the following steps S3 and / or S4 as needed for motion correction, which falls within the scope of the present application.

[0139] Combined with reference Figure 1 and Fig.12 , step S2 may include: acquiring detection data with depth of interaction (DOI) information to determine the response line endpoint position data of the event. In these embodiments, the acquisition of DOI information may be achieved by one or more methods, including but not limited to crystal stacking method, double-end readout method, light distribution method, continuous crystal DOI measurement method, and other known or novel methods for acquiring DOI information.

[0140] Accordingly, the actual deposition position (coordinates) of the coincident event or at least its depth position can be determined based on the depth of action (DOI) information. Accordingly, the line connecting the (actual) deposition positions of the coincident event can be regarded as the flight trajectory of the paired gamma photons corresponding to the coincident event. Alternatively, the line connecting the actual deposition depth and the plane center coordinates of the deposition crystal can be regarded as the flight trajectory of the paired gamma photons corresponding to the coincident event.

[0141] For example, specific reference Fig.12 , when we have the DOI information, we can not only know that the two photons are deposited in crystals 2 and 4 respectively, but also know their deposition depths in crystals 2 and 4. In the two crystals, take their actual deposition positions ( Fig.12 The center point of the plane where the deposition depth is located is connected by a line, which has two intersections with the detection surface of the detector, and the two intersections are located in crystals 1 and 3. Here, the center line of the surface of crystals 1 and 3 can be taken as the corrected LOR (dashed line in the figure). Accordingly, the coordinates of the two ends of the LOR after parallax correction used in the motion correction method of the present application are motion corrected.

[0142] although Figure 1 Not shown, the motion correction method may also include an optional step S0 of preprocessing the detection data (not shown in the figure): preprocessing the detection data obtained by multiple detectors to obtain preprocessed detection data. The preprocessed detection data includes the coincident event data on the response line, such as all the response lines in the detection field of view (FOV).

[0143] In the embodiment of the present application, before the motion correction step (such as step S3) is performed, a preprocessing step may be optionally performed. In a preferred embodiment, the preprocessing step is performed between the acquisition of detection data step S2 and the motion correction step S3 described below.

[0144] By way of explanation and not limitation, after a detector of a PET device, such as a PET system, a PET / CT system, or a PET / MR system, scans a target object, matching events on response lines at various projection angles within the FOV of the detector may be acquired as acquired detection data, such as acquired PET data.

[0145] In a preferred embodiment of the present application, detection data on all response lines at all projection angles can be obtained. These detection data are in list mode, for example. Fig.19As shown, it may include, for example, time information, energy information, position information and other information that conform to the event. As an explanation, the position information that has not been corrected by the motion correction scheme of the embodiment of the present application is, for example, the response line endpoint position information, which may or may not include the deposition depth (DOI information) in different embodiments of the present application, as further described below.

[0146] In an alternative embodiment of the present application, all response lines at all projection angles may be combined to obtain an uncorrected sinogram.

[0147] In an embodiment of the present application, the collected detection data is preprocessed by scattering correction, random correction, attenuation correction, and normalization correction to obtain preprocessed detection data. For example, a delay time window method can be used to perform random correction. The preprocessing means can be performed using known or novel preprocessing means, and the present application is not limited to this. In addition, other preprocessing can also be imagined, which falls within the scope of the present application. As an illustration, in some embodiments of the present application, certain optional method steps can be selectively executed or not executed according to the preprocessing situation.

[0148] In an embodiment of the present application, in the preprocessing step, known motion correction methods described elsewhere in this document can be selectively performed, such as the motion correction methods proposed above for data loss caused by movement out of the detection range, such as the methods described in the literature by P. Bühler, VW Zhou or A. Rahmim.

[0149] As a supplement or alternative to the pre-processing step, the second correction data described below can be processed in a post-processing step S0' (not shown in the figure), for example, one or more of the above-mentioned scatter correction, random correction, attenuation correction and normalization correction as well as the motion correction means proposed for data loss caused by movement out of the detection range are performed, all of which fall within the scope of the present application.

[0150] S3: performing motion correction on at least part of the conforming event data on the response line according to the motion trajectory of the target object to obtain first corrected data on the corrected response line.

[0151] In the embodiment of the present application, the first correction data will include correction response line endpoint position data.

[0152] Specifically, Figure 3 As shown, step S3 may include:

[0153] S31: determining a reference detection position among a plurality of detection positions of the motion trajectory;

[0154] S32: performing spatial transformation on the response line endpoint positions on the response lines at the other detection positions according to the motion trajectories of the other detection positions relative to the reference detection position, to obtain the corrected response line endpoint positions.

[0155] In addition, in an optional step, the detection data at the reference detection position may not be subjected to motion correction and may be directly used for image reconstruction. Here, the method of the embodiment of the present application may also include an optional step S3' (not shown in the figure): using the coincident event data on the response line at the reference detection position as non-corrected data for image reconstruction.

[0156] The spatial position transformation of step S32 can be referred to, for example, Fig.13 As shown in the schematic diagram, for example, based on the motion information between the detection position corresponding to the response line LOR2 and the reference detection position corresponding to the response line LOR1 (the line connecting the endpoints PA1 and PA2), the endpoints PA1' and PA2' of the response line LOR2 can be corrected to the reference detection position to obtain the corrected response line endpoint position ( Fig.13 Similarly, based on the motion information between the detection position corresponding to the response line LOR3 and the reference detection position corresponding to the response line LOR1, the endpoints PA1” and PA2” of the response line LOR3 can be corrected to the reference detection position to obtain the corrected response line endpoint position ( Fig.13 (not shown). Fig.14 As shown, the response line endpoint positions p1(x1, y1, z1) and p2(x2, y2, z2) of the response line p1p2 at other detection positions that meet the event are transformed to obtain the corrected response line q1q2 endpoint positions q1(x1', y1', z1') and q2(x2', y2', z2'). As an illustration, the (motion) corrected response line described in step S3 and its sub-steps herein is not a real response line, but a line segment obtained after the original response line is transformed in endpoint space.

[0157] In addition, if Fig.13 As shown, coincident event data on the response line at the reference detection position (eg, end points PA1 and PA2 of the response line LOR1) can be directly used as non-corrected data for image reconstruction.

[0158] Combination Figure 2 In the embodiment shown, step S3 and its sub-steps S31 and S32 can be performed based on data frames. In other words, the determination of the reference detection position in step S3, more specifically step S31, can be determined by directly determining the reference (initial) data frame; and the spatial transformation of other detection positions in step S3, more specifically step S32, can be performed directly based on motion information between different data frames.

[0159] Accordingly, in a specific embodiment, the above step S2 may include: dividing the detection data into multiple data frames corresponding to multiple detection positions; the above step S31 may include: determining a reference frame among the multiple data frames, and the target object is located at the reference detection position in the reference frame; the above step S32 may include: based on the motion information of other data frames relative to the reference frame, spatially mapping each response line that meets the event in each of the other data frames, and converting it into a correction response line corresponding to the reference frame.

[0160] Combined with reference Figure 2 and Fig.13 When the detection data is divided into a plurality of data frames corresponding to a plurality of detection positions, assuming that N=100 frames, the relative motion information between the data frames can be determined according to the relative motion information between the corresponding image frames (M≥N) or the stored given motion trajectory. Figure 2 If the initial (reference) image frame of the image frame corresponds to the reference (data) frame, the relative motion information of other data frames relative to the reference (data) frame can be determined by the relative motion information of other image frames corresponding to other data frames relative to the initial (reference) image frame, for example, by the RT matrix between them. As an example, for a matching event located on the response line of other data frames, the response line endpoint position (coordinate matrix) of the matching event can be processed by the RT matrix to obtain the corrected response line endpoint position (coordinate matrix). For example Fig.14 As shown, the response line endpoint positions p1(x1, y1, z1) and p2(x2, y2, z2) located in other data frames are transformed to obtain the correction response line (segment) q1q2 endpoint positions q1(x1', y1', z1') and q2(x2', y2', z2') of the corresponding reference (data) frame.

[0161] S4: Determine second correction data for image reconstruction according to intersection information between the correction response line of the first correction data and the detector and / or the virtual detector.

[0162] In the embodiments of the present application, the multiple detectors included in the PET device are physical detectors. In this article, unless otherwise specified as a "virtual" detector, the detector refers to a physical detector; similarly, unless otherwise specified, a crystal will refer to a physical crystal, and other features are similar. In some embodiments, the physical detector may include a crystal array and a photoelectric conversion element. The crystal array may include a crystal array surface, which can be used as a detection surface.

[0163] As mentioned above, in the embodiment of the present application, the PET device is also provided with at least one virtual detector. It will be understood that the virtual detector is "virtual", so it does not collect detection data, such as photon deposition position data, energy data, time data, etc. However, when the detection data is motion corrected and used for subsequent image reconstruction, the virtual detector will be taken into account. In the embodiment described in step S4, the second corrected data that intersects with the virtual detector based on motion correction will be regarded as the data "detected" by the virtual detector.

[0164] In different embodiments of the present application, the virtual detector has a variety of different implementation forms, and can be implemented in a variety of different devices, units, equipment, programs, modules, and can be implemented in software, hardware, firmware or a combination thereof. In some embodiments, the virtual detector can be implemented in one or more computers possessed by the PET device, and in other embodiments, the virtual detector can be implemented in a remote computer connected to the PET device. In some embodiments, the virtual detector can be implemented by a program function module; in other embodiments, the virtual detector can be implemented by a simulation module or software. In some preferred embodiments, the virtual detector may also have a visualization module, which is presented as part of the detector structure, for example, in a user interface or a visualization interface. For ease of description, Figures 4 to 11C The structure of the "virtual" detector is presented in a visual manner, but it will be understood that in other embodiments of the present application, the "virtual" detector may have the virtual detector functions shown in the drawings, but they are not visible.

[0165] In the embodiment of the present application, similar to the detector, the virtual detector may include a virtual crystal array having a virtual detection surface, and the virtual detection surface is, for example, the surface of the virtual crystal array.

[0166] However, in an alternative embodiment of the present application, due to the “virtual” nature, the virtual detector can be simplified to a crystal array surface of a virtual crystal array, that is, the virtual detector can be composed of a virtual detection surface of a virtual crystal array.

[0167] In the embodiment of the present application, the virtual detector may have different forms according to the detector structure and different needs.

[0168] In an embodiment of the present application, a plurality of detectors circumferentially surround the target object, and at least one virtual detector includes an end virtual detector located at at least one axial end of the plurality of detectors. In a preferred embodiment, the at least one virtual detector includes a pair of end virtual detectors located at both ends of the axial direction of the plurality of detectors.

[0169] In the embodiment of the present application, the axial direction has the conventional definition in the art, and may also be referred to as the z direction. For example, the direction of the axis around which the detector of the PET device is surrounded is the axial direction, and the radial direction and the circumferential direction may be determined accordingly based on the axial direction. Figure 6 , Figure 7 , Figure 8 , Fig. 9A , Fig. 9B , Fig.10 , Fig. 11C In the detector structure of the PET device shown, the direction perpendicular to the paper surface can be defined as the axial direction.

[0170] refer to Figure 4 , shows a PET device 400, which has a multi-panel detector structure, specifically a four-panel detector structure. Figure 4 As shown, the PET device 400 may include a plurality of detectors 410, which may include a crystal array. It will be appreciated that the detectors or components thereof may have different sizes as desired, which all fall within the scope of the present application.

[0171] Continue to refer Figure 4 The PET device can also be provided with virtual detectors located at one or both ends (shown as both ends) of the detector axis, which are end virtual detectors 420, 420'. Figure 4 As shown, the end virtual detectors 420, 420' have a polygonal shape corresponding to the end opening of the space enclosed by the multi-panel detectors, which is a quadrilateral shape in this case. It will be understood that the corresponding end opening will cover a variety of possibilities, such as aligning with the outer diameter of the end opening (such as Figure 4 As shown), aligned with the inner diameter (as Figure 5 The size is between the outer diameter and the inner diameter, such as slightly larger than the inner diameter (such as Figures 6 to 8 As shown), it can also be slightly larger than the outer diameter, which falls within the scope of the present application.

[0172] exist Figure 4 In the illustrated embodiment, the virtual detector may include a virtual crystal array having a virtual detection surface, which is shown in darker colors. However, it is contemplated that the virtual detector may be simplified to a virtual detection surface of a virtual crystal array, thereby obtaining new embodiments.

[0173] Continue to refer Figure 5 , shows a PET device 500, which has a multi-panel detector structure, specifically a four-panel detector structure. Figure 5 As shown, the PET device 500 may include a plurality of detectors 510 , and the detectors 510 may include a crystal array.

[0174] Continue to refer Figure 5The PET device can also be provided with a virtual detector located at one or both ends (one end is shown in the figure) of the detector axis, which is an end virtual detector 520. Figure 5 In the illustrated embodiment, the size of the end dummy detector 520 is aligned with the inner diameter of the end opening of the detector structure. Figure 5 In the illustrated embodiment, the virtual detector is simplified to a virtual detection surface of a virtual crystal array, i.e., a crystal array surface, which is shown as a darkened grid array in the figure. However, it is conceivable that the virtual detector may include a virtual crystal array with a virtual detection surface, thereby obtaining a new embodiment.

[0175] refer to Figure 6 The PET device 600 shown in FIG. 1 has a multi-panel detector structure, specifically a four-panel detector structure. Figure 6 As shown, the PET device 600 may include a plurality of detectors 610. Figure 6 In the illustrated embodiment, the virtual detector is an end virtual detector 620 , which is simplified by dashed lines and has a size (or detection coverage area) slightly larger than the end opening (inner diameter) of the flat detection structure.

[0176] refer to Figure 7 The PET device 700 shown in FIG. 1 has a multi-panel detector structure, specifically a six-panel detector structure. Figure 7 As shown, the PET device 700 may include a plurality of detectors 710. Figure 7 In the illustrated embodiment, the virtual detector is an end virtual detector 720, which is simplified by dashed lines and has a size (or detection coverage area) slightly larger than the end opening (inner diameter) of the flat detection structure.

[0177] In some embodiments, a PET device may include a ring-shaped detector.

[0178] refer to Figure 8 The PET device 800 shown has a ring-shaped detection structure 810. Figure 8 As shown, the annular detection structure of the PET device 800 may include multiple detectors. Figure 8 In the illustrated embodiment, the virtual detector is an end virtual detector 820, which is simplified by dashed lines. The size or detection coverage area of ​​the virtual detector is slightly larger than the circular end opening (inner diameter) of the annular detection structure.

[0179] In some embodiments of the present application, the plurality of detectors only partially surround the target object in the circumferential direction, and the at least one virtual detector includes a circumferential virtual detector arranged in the circumferential non-surrounding area of ​​the plurality of detectors. In these embodiments, a virtual detector may also be provided, further comprising one or two end virtual detectors located at one or both axial ends of the plurality of detectors and the circumferential virtual detector.

[0180] refer to Fig. 9A , shows a PET device 900, which has a multi-flat panel detection structure with a notch, specifically a "four" flat panel detection structure with a circumferential notch. As shown in FIG9 , the PET device 900 may include three detectors 910, and the three detectors 910 constitute a "four" flat panel detector structure with a notch.

[0181] Continue to refer Fig. 9A The PET device 900 may also be provided with a circumferential virtual detector 920 (indicated by a dotted line) located in the circumferential gap. The circumferential virtual detector 920 has the same shape as the detector 910 and completes the circumferential gap of the "four" flat plate detection structure.

[0182] In the embodiment of the present application, the simplified virtual detector can also be used as a circumferential virtual detector.

[0183] Combined with reference Fig. 9B and Fig. 9C , shows a PET device 900', which has a multi-plate detection structure with notches, specifically a "four" plate detection structure with circumferential notches. Fig. 9B As shown, the PET device 900' may include three detectors 910', and the three detectors 910' constitute a "quad" flat panel detector structure with a gap.

[0184] Continue to refer Fig. 9B The PET device 900' can also be provided with a circumferential virtual detector 920' located in the circumferential gap. The circumferential virtual detector 920' has the same shape as the detector 910 and completes the circumferential gap of the "four" flat plate detection structure. More specifically, as Fig. 9B As shown, the circumferential virtual detector 920' (indicated by dotted lines) is simplified to be composed of a virtual detection surface of a virtual crystal array, and the shape of the virtual detection surface of the virtual detector 920' is the same as the detection surface shape of the detector 910, more specifically, the same as the detection surface shape of the opposite detector. Fig. 9C A virtual detector 920' is shown simplified to a virtual detection surface, which is shown as a grid array.

[0185] In the various embodiments described in the present application, the “shape” of the virtual detector may involve a planar shape or a three-dimensional shape, and may include one or more component shapes or the overall shape of the detector. For example, when the virtual detector is simplified to a virtual detection surface, the same shape may refer to the virtual detection surface being the same (planar) shape as the detection surface of other (physical) detectors (e.g. Fig. 9B Alternatively, when the virtual detector includes a virtual crystal array, the same shape may mean that the virtual crystal array of the virtual detector has the same (three-dimensional) shape as the crystal array of other (physical) detectors (e.g. Fig. 9A ); or, the virtual detector can be overall the same shape as other physical detectors (stereoscopic).

[0186] refer to Fig.10 , shows a PET device 1000, which has a multi-plate detection structure with notches, specifically a "six" plate detection structure with circumferential notches. Fig.10 As shown, the PET device 1000 may include five detectors 1010 , and the five detectors 1010 form a “six” flat panel detector structure with a gap.

[0187] Continue to refer Fig.10 The PET device 1000 may also be provided with a circumferential virtual detector 1020 (indicated by a dotted line) located in the circumferential gap. The circumferential virtual detector 1020 has the same shape as the detector 1010 and completes the circumferential gap of the "six" flat plate detection structure.

[0188] refer to Fig.11A , shows a PET device 1100, which has a partial annular detection structure 1110 with a circumferential notch. The partial annular detection structure 1110 can, for example, have a segmental circumferential notch around an angle α.

[0189] Continue to refer Fig. 11B The PET device 1100 may also be provided with a circumferential virtual detector 1120 (indicated by a dotted line) located in the circumferential gap. The circumferential virtual detector 1120 has a ring segment shape that fills the circumferential gap and may have a surrounding angle of 360°-α.

[0190] Fig. 11C It is shown that the circumferential virtual detector 1120 fills the circumferential gap of the partial annular detection structure 1110.

[0191] The PET devices of the various embodiments described above may be combined into embodiments of different methods or steps thereof to obtain new embodiments.

[0192] Continue to refer Figure 1In the embodiment of the present application, the second correction data includes correction intersection position data. In this article, the correction intersection position is interpreted broadly, including both the actual intersection position and other positions in the intersecting crystal, as further described below.

[0193] In an embodiment of the present application, step S4 may include: determining an actual intersection position of the correction response line and / or its extension line with the detection surface of the detector and / or the virtual detection surface of the virtual detector as the correction intersection position.

[0194] Continue to refer Fig.14 After the correction response line (segment) q1q2 endpoint positions q1(x1', y1', z1'), q2(x2', y2', z2') of the corresponding reference (data) frame are obtained through transformation, the intersection points m1(x3, y3, z3), m2(x4, y4, z4) of the correction response line (segment) or its extension with the crystal of the detector, more specifically the crystal surface (detection surface) or the virtual crystal surface (virtual detection surface) of the virtual detector can be determined. In these embodiments, the second correction data for image reconstruction can be obtained based on whether it intersects with the detector (detection surface) or the virtual detector (virtual detection surface), for example, both ends intersect with the detector, both ends intersect with the virtual detector, one end intersects with the detector and the other end intersects with the virtual detector. In an embodiment of the present application, at least part of the second correction data is determined based on the intersection information with the virtual detector.

[0195] In these embodiments, the actual intersection point position of the actual intersection will be used for image reconstruction as the corrected intersection point position included in the second correction data.

[0196] In an alternative embodiment of the present application, step S4 may include: determining the crystal and / or virtual crystal at which the correction response line and / or its extended line intersects with the detection surface of the detector and / or the virtual detection surface of the virtual detector, and taking the center of the intersecting crystal and / or virtual crystal as the correction intersection position.

[0197] Continue to refer Fig.14After the correction response line (segment) q1q2 endpoint positions q1(x1', y1', z1'), q2(x2', y2', z2') of the corresponding reference (data) frame are obtained through transformation, the intersection information of the correction response line (segment) or its extension with the crystal of the detector, more specifically the crystal surface (detection surface) or the virtual crystal surface (virtual detection surface) of the virtual detector can be determined, such as the intersection points m1(x3, y3, z3) and m2(x4, y4, z4), and then which crystal and / or virtual crystal intersects with the correction response line (segment) or its extension. And the center of the intersecting crystal and / or virtual crystal is determined accordingly, such as m1'(x3', y3', z3') and m2'(x4', y4', z4'). In these embodiments, the center position of the intersecting crystal / virtual crystal will be used as the correction intersection position included in the second correction data for image reconstruction.

[0198] In these alternative embodiments, it will be appreciated that when the virtual detector is simplified to a virtual detection surface of a virtual crystal array, the intersecting crystals can still be determined, for example, by determining which grid in a planar grid array intersects, as shown in FIG. Figure 5 and Fig. 9C .

[0199] By this, for example, the corrected intersection positions m1(x3, y3, z3), m2(x4, y4, z4) or m1'(x3', y3', z3'), m2'(x4', y4', z4') can be used accordingly for updating the list (Listmode) format ( Fig.19 ) in the coincidence event data for image reconstruction. In addition, if the response lines p1p2 are located at the reference detection position (located at the reference frame), the original coincidence event data containing the response line endpoint positions p1(x1, y1, z1) and p2(x2, y2, z2) can be directly used for image reconstruction without any motion change.

[0200] refer to Fig.15 , the embodiment of the present application also provides an image reconstruction method, which may include:

[0201] S1510: Detecting a moving target object using multiple detectors to obtain detection data;

[0202] S1520: Process the detection data using the motion correction method according to the first aspect to obtain second correction data;

[0203] S1530: Reconstruct an image using the processed detection data, wherein the processed detection data includes second corrected data and optional non-corrected data (as described below).

[0204] Accordingly, in the embodiment of the present application, the image reconstruction method further includes an optional step S1520':

[0205] S1520': Acquire non-corrected data using the motion correction method according to the embodiment of the present application.

[0206] At this time, the processed detection data in step S1530 includes the second correction data and optional non-correction data.

[0207] As mentioned above, reference Fig.19 In a preferred embodiment, the processed detection data is detection data in a list mode format. For example, the position information in the detection data in the list mode format updates the corrected intersection positions m1(x3, y3, z3), m2(x4, y4, z4) or m1'(x3', y3', z3'), m2'(x4', y4', z4') or retains the original response line endpoint positions p1(x1, y1, z1), p2(x2, y2, z2).

[0208] In an alternative embodiment, the image reconstructed data is a sinogram. Here, before the image reconstruction, the image reconstruction method includes: setting a sinogram encoding for the processed detection data; and processing the processed detection data based on the sinogram encoding to obtain detection data in the form of a sinogram.

[0209] By way of explanation and not limitation, list mode data is a sequence of matching events in the detection data, usually but not necessarily in chronological order; and sinogram data can be viewed as a histogram of list mode data, i.e., the row counts of list mode data located on the same line of response (LOR) are accumulated.

[0210] Accordingly, if image reconstruction is performed based on a sinogram, a sinogram encoding for converting from a position coordinate or list format to a sinogram format can be set accordingly for the second correction data including the correction intersection position and optional non-correction data, and the processed detection data (the second correction data and optional non-correction data) can be converted into a sinogram based on the sinogram encoding.

[0211] In the embodiments of the present application, image reconstruction may adopt any suitable known or novel image reconstruction algorithm, including but not limited to (filtered or direct) back projection, maximum likelihood expectation maximization (ML-EM), ordered subset expectation maximization (OSEM), etc., which all fall within the scope of the present application.

[0212] like Fig.16 As shown, in an embodiment of the present application, a motion correction device 1600 is also provided, which can be applied to a PET device, wherein the PET device includes a plurality of detectors and defines at least one virtual detector.

[0213] like Fig.16 As shown, the motion correction device 1600 may include: an acquisition unit 1610, configured to acquire detection data obtained by detecting a moving target object by the multiple detectors, the detection data including coincident event data on a response line; a first correction unit 1620, configured to perform motion correction on at least part of the coincident event data on the response line according to the motion trajectory of the target object, to obtain first correction data on the corrected response line; and a second correction unit 1630, configured to determine second correction data for image reconstruction according to intersection information of a corrected response line of the first correction data with the detector and / or the virtual detector.

[0214] In addition, if Fig.17 As shown, in an embodiment of the present application, an image reconstruction device is also provided, which may include: a detection unit 1710, configured to use multiple detectors to detect a moving target object to obtain detection data; a motion correction unit 1720, configured to process the detection data using the motion correction method described in the embodiment of the present application to obtain second correction data; an image reconstruction unit 1730, configured to perform image reconstruction using the processed detection data, and the processed detection data includes the second correction data.

[0215] Accordingly, for example Figures 4 to 11C As schematically shown, an embodiment of the present application also provides a PET device, which includes multiple detectors and a motion correction unit (not identified); wherein the PET device is also limited to at least one virtual detector; wherein the motion correction unit is configured to implement the motion correction method described in the embodiment of the present application.

[0216] Those skilled in the art will understand that the devices and apparatuses described in the embodiments of the present application can be combined with the method features described in the embodiments of the present application, and vice versa.

[0217] The embodiments of the present application also relate to electronic devices capable of implementing the methods of the embodiments of the present application.

[0218] In some embodiments, an electronic device is provided, which may include a processor and a memory storing a computer program, wherein the processor is configured to execute the method of any embodiment of the present application when running the computer program.

[0219] Fig.18A schematic diagram of an exemplary electronic device 1800 that can implement the method of the embodiment of the present application is shown, which may include more or fewer electronic devices than shown in the figure in some embodiments. In some embodiments, it can be implemented using a single or multiple electronic devices. In some embodiments, it can be implemented using cloud or distributed electronic devices.

[0220] like Fig.18 As shown, the electronic device 1800 includes a processor 1801, which can perform various appropriate operations and processes according to the programs and / or data stored in the read-only memory (ROM) 1802 or the programs and / or data loaded from the storage part 1808 to the random access memory (RAM) 1803. Processor 1801 can be a single-core or multi-core processor, or it can include multiple processors. In some embodiments, processor 1801 may include a general-purpose main processor (such as a CPU) and one or more special coprocessors, such as a graphics processing unit (GPU), a neural network processor (NPU), a digital signal processor (DSP) or other general or application-specific integrated circuits. In RAM1803, various programs and data required for the operation of electronic device 1800 are also stored. Processor 1801, ROM1802 and RAM 1803 are connected to each other via bus 1804. Input / output (I / O) interface 1805 is also connected to bus 1804.

[0221] The processor and the memory are used together to execute the program stored in the memory. When the program is executed by the computer, the steps or functions of the methods described in the above embodiments can be implemented.

[0222] The following components are connected to the I / O interface 1805: an input section 1806 including a keyboard, a mouse, etc.; an output section 1807 including a display and a speaker, etc.; a storage section 1808 including a hard disk, etc.; and a communication section 1809 including a network interface card such as a LAN card, a modem, etc. The communication section 1809 performs communication processing via a network such as the Internet. A drive 1810 is also connected to the I / O interface 1805 as needed. A removable medium 1811, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 1810 as needed, so that a computer program read therefrom is installed into the storage section 1808 as needed.

[0223] Fig.18 Only schematically illustrated are schematic electronic devices, but the electronic devices according to the embodiments of the present application may include Fig.18 The electronic device shown may have more or fewer components or may have Fig.18 The devices of the illustrated embodiments may have the same, partially the same or different architectures.

[0224] In some embodiments, the electronic device may be combined with various components to obtain a method, device, and system having the advantages of the present invention.

[0225] Although not shown, in some embodiments, a computer-readable storage medium is also provided, storing a computer program, which is configured to execute any method of the present application embodiment when it is run. The computer program includes various program modules / units constituting the device according to the embodiment of the present application, and the computer program composed of various program modules / units can realize the functions corresponding to the various steps in the method described in the above embodiment when it is executed. The computer program can also be run on an electronic device as described in the embodiment of the present application.

[0226] The storage medium of the embodiment of the present application includes non-volatile and / or volatile articles that can be used to store information by any method or technology. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0227] Those skilled in the art should understand that the embodiments of this specification can be implemented in various forms such as methods, systems or computer program products. Therefore, those skilled in the art can imagine that the implementation of the functional modules / units or controllers and related method steps described in the above embodiments can be implemented in software, hardware or a combination of software / hardware.

[0228] Unless explicitly stated, the actions or steps of the methods, programs, and embodiments of the present application do not have to be performed in a specific order and can still achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0229] In this article, multiple embodiments are described, but for the sake of simplicity, the description of each embodiment is not exhaustive, and the same or similar features or parts between the embodiments may be omitted. In this article, "one embodiment", "some embodiments", "example", "specific example", or "some examples" are meant to be applicable to at least one embodiment or example according to the present application, rather than all embodiments. The above terms do not necessarily mean to refer to the same embodiment or example. In the absence of contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples.

[0230] The exemplary systems and methods of the present application have been specifically shown and described with reference to the above embodiments, which are merely examples of the best modes for implementing the present systems and methods. It will be appreciated by those skilled in the art that various changes may be made to the embodiments of the systems and methods described herein when implementing the present systems and / or methods without departing from the spirit and scope of the present invention as defined in the appended claims.

Claims

1. A motion correction method, applied to a PET device, characterized in that: The PET device includes a plurality of detectors and defines at least one virtual detector; the motion correction method includes: Acquire detection data obtained by the plurality of detectors detecting the moving target object, wherein the detection data includes coincident event data on the response line; According to the motion trajectory of the target object, motion correction is performed on at least part of the coincident event data on the response line to obtain first corrected data on the corrected response line; and Second correction data for image reconstruction is determined based on intersection information between the correction response line of the first correction data and the detector and / or the virtual detector, wherein at least part of the second correction data is determined based on the intersection information with the virtual detector.

2. The motion correction method according to claim 1, characterized in that: The event-compliant data includes response line endpoint position data that corresponds to the event; the first correction data includes corrected response line endpoint position data; and the second correction data includes corrected intersection position data.

3. The motion correction method according to claim 2, characterized in that: The acquiring detection data obtained by the multiple detectors detecting the moving target object includes: Acquire detection data with depth of interest (DOI) information to determine the response line endpoint data of the coincident event.

4. The motion correction method according to claim 2, characterized in that: The step of performing motion correction on at least a portion of the conforming event data on the response line according to the motion trajectory of the target object to obtain first corrected data on the corrected response line includes: determining a reference detection position among a plurality of detection positions of the motion trajectory; According to the motion trajectory of other detection positions relative to the reference detection position, the response line endpoint positions on the response lines of the other detection positions are spatially transformed to obtain the corrected response line endpoint positions.

5. The motion correction method according to claim 4, characterized in that: The motion correction method further comprises: The coincident event data located on the response line of the reference detection position is used as non-corrected data for image reconstruction.

6. The motion correction method according to claim 4, characterized in that: The acquiring detection data obtained by the multiple detectors detecting the moving target object includes: dividing the detection data into a plurality of data frames corresponding to a plurality of detection positions; The step of determining a reference detection position among a plurality of detection positions of the motion trajectory comprises: Determining a reference frame among the plurality of data frames, wherein the target object is located at the reference detection position in the reference frame; The step of spatially transforming the response line endpoint position on the response line of the other detection positions according to the motion trajectory of the other detection positions relative to the reference detection position to obtain the corrected response line endpoint position includes: According to the motion information of other data frames relative to the reference frame, each response line that meets the event in each of the other data frames is spatially mapped and converted into a correction response line corresponding to the reference frame.

7. The motion correction method according to claim 1, characterized in that: Determining second correction data for image reconstruction according to intersection information of the correction response line of the first correction data with the detector and / or the virtual detector comprises: The actual intersection position of the correction response line and / or its extension line with the detection surface of the detector and / or the virtual detection surface of the virtual detector is determined as the correction intersection position.

8. The motion correction method according to claim 1, characterized in that: Determining second correction data for image reconstruction according to intersection information of the correction response line of the first correction data with the detector and / or the virtual detector comprises: Determine the crystal and / or virtual crystal where the correction response line and / or its extension line intersects with the detection surface of the detector and / or the virtual detection surface of the virtual detector, and take the center of the intersecting crystal and / or virtual crystal as the correction intersection position.

9. The motion correction method according to claim 1, characterized in that: The method for determining the motion trajectory of the target object includes: Acquiring a plurality of captured images of the moving target object; extracting two-dimensional feature points from the plurality of captured images; Matching the two-dimensional feature points of the multiple captured images and converting them into three-dimensional feature points; The three-dimensional feature points of different image frames of the plurality of captured images are matched to construct a rotation-translation (RT) matrix representing relative motion information of the different image frames.

10. The motion correction method according to claim 1, characterized in that: Also includes: The target object is made to move along a given motion trajectory, and the motion trajectory is stored.

11. An image reconstruction method, characterized in that: include: Using multiple detectors to detect the moving target object to obtain detection data; Processing the detection data using the motion correction method according to any one of claims 1 to 10 to obtain second correction data; An image reconstruction is performed using the processed detection data, the processed detection data including the second correction data.

12. The image reconstruction method according to claim 11, characterized in that: Also includes: Acquiring non-corrected data using the motion correction method according to claim 5; The processed detection data includes the second corrected data and the non-corrected data.

13. The image reconstruction method according to claim 11 or 12, characterized in that: The processed detection data is detection data in a list (List mode) format.

14. The image reconstruction method according to claim 11 or 12, characterized in that: Before image reconstruction, it also includes: setting a sinusoidal pattern encoding for said processed detection data; Based on the sinusoidal encoding, the processed detection data is processed to obtain detection data in a sinusoidal form.

15. A motion correction device, applied to PET equipment, characterized in that: The PET device includes a plurality of detectors and defines at least one virtual detector; The motion correction device comprises: an acquisition unit configured to acquire detection data obtained by the plurality of detectors detecting the moving target object, wherein the detection data includes coincident event data on the response line; A first correction unit is configured to perform motion correction on at least part of the coincident event data on the response line according to the motion trajectory of the target object to obtain first correction data on the corrected response line; and The second correction unit is configured to determine second correction data for image reconstruction according to intersection information between the correction response line of the first correction data and the detector and / or the virtual detector.

16. The motion correction device according to claim 15, characterized in that The plurality of detectors circumferentially surround the target object, and the at least one virtual detector includes an end virtual detector located at at least one end in an axial direction.

17. The motion correction device according to claim 16, characterized in that: The at least one virtual detector includes a pair of end virtual detectors located at two ends of the axial direction.

18. The motion correction device according to claim 16 or 17, characterized in that: The plurality of detectors are multi-panel detectors or annular detectors, and the end virtual detector has a shape corresponding to an end opening of the multi-panel detector.

19. The motion correction device according to claim 15, characterized in that: The plurality of detectors only partially surround the target object in a circumferential direction, and the at least one virtual detector includes a circumferential virtual detector disposed in a circumferential non-surrounding area of ​​the plurality of detectors.

20. The motion correction device according to claim 19, characterized in that The at least one virtual detector further includes one or two end virtual detectors located at one or both axial ends of a detection ring formed by the multiple detectors and the circumferential virtual detector.

21. The motion correction device according to claim 19, characterized in that The multiple detectors are multi-flat panel detectors with circumferential notches, and the circumferential virtual detector has the same shape as the detectors and completes the circumferential notches.

22. The motion correction device according to claim 19, characterized in that The multiple detectors are partial annular detectors with circumferential gaps, and the circumferential virtual detector has a ring segment shape that fills the circumferential gap.

23. The motion correction device according to claim 15, characterized in that Each of the detectors includes a crystal array having a detection surface, and the virtual detector includes a virtual crystal array having a virtual detection surface, or the virtual detector is composed of a virtual detection surface of a virtual crystal array.

24. An image reconstruction device, characterized in that: include: A detection unit is configured to detect a moving target object using a plurality of detectors to obtain detection data; a motion correction unit configured to process the detection data using the motion correction method according to any one of claims 1 to 10 to obtain second correction data; The image reconstruction unit is configured to perform image reconstruction using the processed detection data, wherein the processed detection data includes the second correction data.

25. A PET device, characterized in that: The PET device includes a plurality of detectors and a motion correction unit; Wherein, the PET device is further defined to have at least one virtual detector; The motion correction unit is configured to implement the motion correction method according to any one of claims 1 to 10.

26. An electronic device, characterized in that: include: A processor and a memory storing a computer program, wherein the processor is configured to implement the method according to any one of claims 1 to 14 when running the computer program.

27. A storage medium, characterized in that: The storage medium stores a computer program, and the computer program is configured to implement the method according to any one of claims 1 to 14 when executed.

Images